From Origin to Screen: The Case for Complete Streaming Observability

TL;DR

• Video playback observability captures QoE metrics like buffering events, startup time, and error codes, but it can’t identify whether the root cause is a CDN cache miss, a degraded edge node, or a network routing issue between the origin and the viewer.
• CDN logs reveal cache hit ratios, origin pull rates, request latency, edge node health, and geographic traffic distribution, the critical signals needed to understand what’s happening between the origin server and the end user.
• During major live events, CDNs generate terabytes of log data per hour. Most platforms respond by sampling or pre-aggregating this data, creating blind spots that slow down incident response at the worst possible moments.
• Bitmovin’s Observability surfaces when and how viewers are impacted; Hydrolix CDN Insights identifies where in the delivery infrastructure the issue originated.
• The combination also powers smarter multi-CDN routing decisions, better ad delivery diagnostics, long-term capacity planning, and reduced operational cost.

For streaming platforms, delivery quality is a major revenue and brand issue. Buffering, slow player startup times, and black screens frustrate end users and lead to churn. The pressure is on ops and site reliability teams to find and fix issues quickly, but modern streaming pipelines are extraordinarily complex. These pipelines generate massive volumes of data across every layer, including CDN, encoder, player, and ad delivery. The scale and velocity of this data can be overwhelming. How do you quickly find and fix issues when every second counts?

Observability for video playback provides visibility into the viewer experience, but what about the (potentially thousands) of miles between the origin server and the end user? CDNs handle the majority of the world’s internet traffic, but you can’t simply “set and forget” CDN configurations and hope for the best, especially when it comes to major live events.

This post will cover how combining observability for video playback with deep CDN observability gives streaming platforms the complete picture they need to find and fix issues before viewers get frustrated and churn.

Detecting Issues Between the Origin and the Viewer

Video playback observability captures a rich stream of Quality of Experience (QoE) metrics, including startup time, rebuffering events, bitrate changes, error codes, playback duration, dropped frames, and the viewer’s complete session journey.

This data is the ground truth of the viewer experience. You can see when a viewer dropped or when a rebuffering event occurred. If the stream never started, player logs return the error code for the issue. But knowing that an issue occurred and knowing where it originated are two different things.

When a buffering event surfaces in your playback data, the cause could be anywhere between the origin and the viewer. Was there an issue with the internet service provider (ISP), a cache miss that forced a pull from origin, a misconfigured edge node in a specific region, or something else? Playback observability tells you that a viewer experienced a buffering event, but it can’t tell you whether the root cause was a cache miss at the CDN edge, a degraded edge node, or a routing issue between the origin and the viewer.

You need CDN observability to answer these questions.

What CDN Observability Reveals

CDNs provide the backbone of your delivery infrastructure. They are responsible for caching and distributing your content across edge nodes worldwide, and they generate an enormous volume of log data in the process: cache hit ratios, request latency, origin pull rates, byte-range requests, error codes, geographic distribution of traffic, and more.

To make matters more complicated, multi-CDN architectures, which are now standard practice at major streaming platforms, create a dynamic delivery environment where traffic is constantly shifted between providers based on performance signals, cost optimization rules, and failover logic. Understanding how that traffic distribution is performing requires the ability to correlate and compare logs across CDN providers.

Here are just a few critical questions that you can answer with CDN observability:

• Which CDN is performing best for which geography, right now? Multi-CDN routing decisions made without real-time performance data are essentially guesses. CDN log analysis, at sub-minute latency, gives operations teams the signal they need to shift traffic intelligently — or to validate that their automated steering logic is working as intended.
• Where are your cache hit rates degrading? A cache hit ratio drop of even a few percentage points at scale translates directly to origin load, latency increases, and viewer impact. CDN observability catches this before it cascades.
• Are your edge nodes healthy across all regions? Edge node failures can serve some content while silently degrading other content.
• What does your delivery infrastructure look like during a traffic spike? Live events generate log volumes that can be orders of magnitude higher than baseline.
• Which segments were served, from which edge, and at what latency? Did the CDN report errors for any segments?

CDN observability is now a baseline requirement for ensuring QoE and delivering successful events. But most observability platforms have challenges with CDN logs due to their scale and velocity.

The Challenge of CDN Observability

CDN infrastructure generates log data at a scale that most observability platforms weren’t built to handle. During a major live event, CDN observability can generate terabytes of log data per hour. As an example, CDNs generated nearly 200 terabytes of logs during the 2025 Super Bowl over the span of the 3.5 hour game. 

Across a multi-CDN architecture with millions of concurrent viewers, that volume is difficult to ingest, expensive to store, and slow to query for most platforms, forcing teams to make compromises when it comes to the quality of their data.

Some sample their CDN logs, retaining a fraction of the full stream to keep costs manageable. It’s also common to keep that data for a short period of time, making it hard to conduct successful post-mortems and to analyze cyclical patterns in event delivery. Many streaming providers rely on pre-aggregated dashboards from CDN vendors, which provide high-level metrics but don’t let you drill down into your data to understand what’s actually happening.

The consequences can show up at the worst possible moments. When video playback observability flags a regional QoE degradation, you need to know whether the problem is at the CDN edge, the origin, or somewhere in the network path between them. If the CDN log data for that window has been sampled, aggregated, or discarded, that question becomes very difficult to answer quickly. Every second it takes to resolve the issue will lead to more viewer complaints, dissatisfaction, and churn. 

This is the core observability gap for streaming platforms: not the absence of data, but the inability to retain and query it at the fidelity and speed that delivery at scale demands. To solve it, you need a platform designed to handle the scale of CDN data.

Combining Bitmovin and Hydrolix for Streaming Observability

This is how observability for video playback and CDN observability work together. Bitmovin’s Observability tells you when and how viewers are impacted, while CDN Insights from Hydrolix tells you where in the delivery infrastructure the issue originated. Combined, they give streaming platforms complete observability across the full delivery chain.

Here are some of the benefits you get from combining Bitmovin and Hydrolix for streaming observability.

Faster incident response: When playback observability and CDN log data  are combined, engineering teams can move from detecting a viewer impact to identifying its root cause in minutes rather than hours. Either the issue is in the CDN layer and you use techniques like CDN steering to resolve it or you’ve eliminated your network infrastructure as a potential cause of the issue. Engineering teams stop investigating the wrong layer and remediate the right one faster.

Smarter multi-CDN routing: Viewer experience data can surface which regions are being impacted, while CDN log data tells you which provider is underperforming there. You can segment CDN data by region, ISP, ASN, and more so you have a granular understanding of how your CDNs are performing. This makes automated and manual traffic steering decisions more accurate, reducing delivery cost while improving reliability.

Long-term capacity and quality planning: Historical viewer experience data alongside CDN log data retained at scale enables year-over-year comparison of delivery performance, identification of systematic quality issues, and more accurate infrastructure capacity planning ahead of major events.

Ad delivery performance: Bitmovin’s observability surfaces ad startup failures, completion rates, and where ad-related buffering is impacting viewer experience. When those signals point to a delivery issue, Hydrolix CDN log data can pinpoint whether the problem is at the edge, the origin, or somewhere in between. Faster identification of ad delivery failures means less revenue lost during high-demand moments.

Reduced operational cost: Legacy observability platforms often force teams to make compromises when it comes to analyzing and retaining CDN data. Either you sacrifice your data or pay high costs. By combining Bitmovin’s purpose-built video playback observability with CDN observability from Hydrolix, streaming platforms get best-of-breed capabilities at each layer without the overhead of a single monolithic platform.

Conclusion

Viewer expectations for streaming quality have never been higher, and the infrastructure required to meet those expectations has never been more complex. Observability that stops at the CDN edge or only includes the viewer’s playback experience is not enough.

The teams that will deliver the best streaming experiences, and respond fastest when things go wrong, are the ones that have built a bridge between CDN infrastructure visibility and what viewers actually experience. They are the ones treating streaming observability not as two separate dashboards but as a single operational discipline.

That is the vision Bitmovin and Hydrolix share: giving streaming platforms the complete picture, from the CDN edge to the viewer’s screen, so that audiences consistently have a great experience across every device.

Want to learn more about how CDN observability and video playback observability work together? Contact Bitmovin to start the conversation or come find us at NAB in the West Hall, Booth W3323.

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About Hydrolix

Hydrolix is a real-time data platform that provides operational intelligence at massive scale for use cases like CDN monitoring. It includes long-term, full-fidelity retention at a fraction of the cost of legacy solutions, with all data remaining hot for queries regardless of age.

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